Abstract
The purpose of this research is preliminary studies and speculation on a shipwrecked ship off the coast of Talesh city in Gilan province related to the Qajar period. In this regard, field studies and sampling of various parts of the hull (wood, metals, water and soil inside and outside the hull) as well as microorganisms such as fungi and moss on the hull have been done. It is noteworthy that the samples were taken from both the open parts and the buried parts of the hull and the surrounding area. After that, the necessary analyzes were performed. The purpose of collecting and interpreting the data resulting from the analysis in this study is to provide a suitable solution for the protection, restoration and maintenance of this valuable historical monument to be considered at the national level and its location as a special tourist museum site. A region should be given priority and the heritage and cultural value of this work should be heard by foreign and domestic tourists. Therefore, the first step of this research has been field studies, speculations and necessary analyzes in the field of protection and restoration, which in the next stages should be considered by considering the appropriate conditions of maintenance and application of reconstruction processes with special protection instructions. And restoration, this ship should be formed in its original form and the lost parts should be restored. In this study, water samples inside and outside the ship were measured with a pH meter. After performing relevant analyzes, including spectroscopy of samples of wood textures of the hull, the presence of hydrocarbon compounds and petroleum derivatives (bitumen) has been determined from FTIR analysis. Other essential analyzes in this study are microbial tests taken from samples. Analyzing the results obtained from the cross section of the samples, this ship was Russian, which was used to transport petroleum products with a wooden structure made of Russian pine (coniferous leaf). In terms of antiquity and time, during the Qajar period and before that, for unknown reasons, it has blossomed on the shore of Ghorogh in the Talesh section of Gilan province.
Keywords: Russian Shipwreck, Qoroq Coastal, Talesh Region of Guilan Provence, Oil Derivatives, Russian Pine, FT-IR Analysis.

Introduction
The pinnacle of underwater archaeological advances is more related to the time when the Scuba: self-contained underwater breathing apparatus was invented. Figure 1 This discipline has revolutionized underwater, seas, and oceans and has yielded valuable achievements and discoveries (Dekker, David, 1889; Davis, 1955; Quick, 1970). Underwater archeology, especially the study of sunken and wrecked ships, is a field of archeology that has the most expertise in the study and exploration of sunken ships. Its techniques are a combination of archeological and diving techniques to become underwater archeology. Therefore, shipwrecks have sunk on some shores and can be discovered and studied as a valuable historical document (Mireskandari, 1379). Study and research with acquired information from historical shipwrecks with objects sunk on the shores or sunk in the seas and oceans themselves is the expressive language and image of the valuable history and civilizations of many centuries and in the processes and patterns of ancient trade, Transportation and migration bring rich information and also transfer culture, knowledge and civilization to future generations. In the past, human beings have been able to conquer the sea and oceans with the least facilities, and this has been a sign of the genius and continuous efforts of people in ancient times and times (Glisan, 1366; Mireskandari, 1379). Therefore, the study of the history of maritime trade and the structure of the historic ships of the Caspian Sea is a necessity that has not been seriously considered by researchers. In this study, the wood structure as well as the necessary analyzes for wood science and extraction materials as well as microbial tests and environmental factors on this ship were studied and with different technologies such as FT-IR and also with extraction processes with solvents. Organic on the internal samples of this shipwreck, useful results have been obtained, including the presence of petroleum derivatives in the internal parts of the hull. The processes of this research are used as basic studies in order to use the best scientific methods and principles in the next stages for its protection, restoration and implementation of technical maintenance operations.

Material and Method
For initial investigations, ambient humidity and ambient temperature were measured at several points with a data logger to analyze the effect of ambient humidity on damage to the ship’s structure and hull for additional studies. At first, with the necessary inspection and visit to the site, the damages that were visible in the structure and appearance of the work were identified, which include the following: 1- Change in the appearance and texture of the wood used; 2- Corrosion of the surface of the metal (mainly nails) iron ones) used for connections and fastenings; 3- Change in color, shape and texture of the covering and strengthening material of the used wood; 4- Burning of wooden surfaces on the southwest side due to lighting a fire on the side of the ship; 5- Fracture and the lack of parts of the ship’s skeleton in some parts of it; 6- Growth of microorganisms and moss cover on a part of the wooden surfaces that were exposed to stagnant moisture; 7- Accumulation of cement tissue around metal joints and fasteners and its homogenization with joints; 8- The inadequacy of the environmental conditions of the ship’s structure, including humidity and temperature in the parts buried in the sand and the outer parts of the ship; 9- The wear of the wooden surfaces of the outer body of the ship due to the movement of sand particles through the wind can be mentioned. For preliminary investigations, ambient humidity and ambient temperature were measured at several points with a data logger device in order to analyze the impact of ambient humidity on the damage caused to the structure and hull of the ship for further studies. By drying the wood specimen of the ship’s hull to prepare the microtome, the work steps were performed according to the working method and cross sections were prepared from the samples. Russia. Also, Microbial tests with moss and mold on wood and microorganisms have been performed in the microbial environment. The results obtained from the microbial tests of the Bio-microbiology Laboratory are as follows. Necessary analyzes have been performed on wooden samples of ship hull with FTIR to check the structure of wooden structures and effective materials.

Results and Discussion
The identified fungi are Aspergillus niger (Aspergillus niger), Aspergillus flavus and Aspergillus fumigatus (Aspergillus fumigatus) that is worth mentioning that due to the coverage of the entire surface of the plate by Aspergillus fungus, it is possible that some fungi in the environment that have a lower growth rate were not grown and isolated on the subrodextrose agar culture medium. The results of the identification of bacteria grown on nutrient agar medium are Bacillus, Pseudomonas, Flavobacterium, Staphylococcus and Arthrobacter.
Bacteria and fungi lead to the deterioration of wooden works through the production of cellulose and lignin decomposing enzymes in the structure of wood. In this study, all the fungal species identified belonged to the genus Aspergillus. This genus of fungi, which includes more than 300 different species, can be found on a large scale all over the world in different environments, including soil, and they multiply quickly in the right conditions, including access to humidity and the right temperature. The production of different enzymes, including cellulase, by different types of Aspergillus species has been proven, hence the isolation of this group of fungi on wooden works indicates their high potential in destroying organic compounds in wood. On the other hand, it should be noted that due to the high growth power of Aspergillus fungus that quickly covers the entire surface of the culture medium, it was not possible to identify and isolate other possible fungi in the environment.
All the bacterial genera isolated in this study are among the bacteria that are abundantly found in various surveys of environmental samples, including soil, therefore, the isolation of these bacterial genera in this study is not far from the mind. The production of extracellular cellulase enzyme has been proven by some of this group of bacteria, including Bacillus, Pseudomonas, and Flavobacterium. It is worth mentioning that the isolation of the relevant bacteria from wood is the reason for the production of 100% cellulose or lignin decomposing enzymes by them, but in an environment with a high microbial population, microbes can use the organic substances released in the environment by the enzymes extracellular produced by other microorganisms to use for growth and reproduction. In total, the culture results of the relevant samples indicate high bacterial and fungal contamination, which often have a high potential to produce enzymes and substances that damage the structure of wood. 

Conclusion
According to the results obtained from various analyzes, including FT-IR results from samples extracted from the hull of a historic ship in the Ghoroq area of Talesh city in Guilan province, due to its high antiquity and its historical and cultural value in the region in different dimensions Including tourism can be very important, so scientific studies for its protection and reconstruction are among the topics that are currently left on the beach without any protection operations and have been exposed to a variety of natural and unnatural damage. These studies are the source of a suitable solution for following the necessary protection and repair instructions. Therefore, in the beginning of these activities, recognizing the injuries and providing a solution is essential. Through field research and analysis of samples, the wooden structure of the hull was made of coniferous wood from Russia and its use has been active in the transportation of goods, including petroleum derivatives. With the analyzed samples of the in-ship jute texture in FT-IR spectroscopy, most of the parts show the wood texture, but some samples show the presence of hydrocarbon compounds that mainly constitute the structure of kerosene. Therefore, considering that the structure of the main timber of the ship’s hull, in addition to being saturated with water, is full of oil compounds, so it needs special protection and restoration operations to perform the best reconstruction and restoration on these valuable historical monuments. The commercial, economic and cultural history will chart a new path for future economic activities and also serve as a professional tourism center for domestic visitors and foreign tourists.

Acknowledgments 
The cooperation of Mr. Abdulmajid Naderi from the oceanographic research institute in the area of the Qoruq ship in Talash city of Gilan province in field studies and sampling is greatly appreciated. Appreciation is given to the respected Research Assistant of the Cultural Heritage Research Institute who always provide the necessary assistance in the direction of research. We would like to thank the dear experts of the Cultural Heritage Research Institute for the necessary assistance for the analyses. We sincerely thank Mrs. Sahar Nouhi for her help in FT-IR spectroscopy, Dr. Nasreen Nouhi Babajan for the microbial analysis of the samples, and Mrs. Irfan Menesh for her cooperation in the extraction process.
The Authors gratefully acknowledge the support of Research Institute of Cultural Heritage & Tourism, Tehran, Iran. It should also be noted that this program is with license 98102964 on 9/24/2018 with the financial support of the Ports and Maritime Organization and with the participation of the Research Institute of Oceanography and Atmospheric Sciences, by the Research Institute of Cultural Heritage and Tourism of the country
 

Abstract
Predictive models are a component of GIS-based statistical approaches, which hold an important place in archaeological research due to advances in relevant theories and tools. Predictive models, developed through the statistical processing and analysis of environmental variables that influence site location, aid in understanding the cultural and natural landscape of the study area and contribute to the development of plans for improved cultural heritage management. This article, employing a statistical-analytical approach and data from archaeological surveys, aims to present a predictive model for a part of the eastern Kurdistan region where archaeological surveys have not yet been conducted. Prediction modelling was performed using the MaxEnt machine learning method, with eleven factors as natural variables and presence data (areas) required for modelling. The model area was divided into two experimental sections (Bijar and Dehgolan) and a prediction area (Qorveh), as the prediction model for Qorveh city was based on the natural variables and presence data from Bijar and Dehgolan cities. Finally, the prediction map was divided into four classes: very high, high, medium, and low suitability areas. The very high suitability area, which comprises 10% of the total model area, contains 59% of the Iron Age sites in eastern Kurdistan. It was found that vegetation cover, land use, and distance from rivers were among the most influential factors in the model. Also, the initial data in Qorveh indicate that 62% of the sites are located in an area comprising 8% with very high desirability, supporting the accuracy of the prediction. The AUC statistic is 0.836, and the finding value for the model has been calculated as 0.82, which indicates a prediction model with an approach value close to 1.
Keywords: Archaeological Prediction Model, GIS, MaxEnt, Eastern Kurdistan, Iron Age.

Introduction
The use of GIS and statistical modelling to map possible locations of archaeological sites has increased over the past decades. (Stefan & Sîrbu, 2010; Niknami et al., 2007; Alirezaei et al., 2019). Currently, archaeological prediction models are a powerful tool for preventing natural and human damage to historical and cultural resources (Danese et al., 2014), and for increasing the efficiency of archaeological field activities and cultural heritage management (Howard et al., 2016; Balla et al., 2014). Statistical modelling, as a perspective for identifying suitable areas for selecting prehistoric settlements, has been widely used by geographers and archaeologists (Sharafi et al., 2016; Verhagen & Dragut, 2012; Kaimaris, 2018). This method can be effectively considered a form of archaeological exploration. This paper aims to develop a concept for creating a prediction model using the MaxEnt method in the Eastern part of Kurdistan, to evaluate similar studies in archaeology, and to determine settings and suggest ways to optimise such approaches. Simultaneously, using a statistical approach based on GIS, the prediction model, and archaeological survey data from the eastern part of Kurdistan, it identifies the most favourable locations for the formation of Iron Age settlements. Accordingly, using environmental and archaeological data from Bijar and Dehgolan counties, a prediction model for Qorveh county has been developed using the MaxEnt method. Due to the lack of access to archaeological data for Qorveh County, the study area has been divided into two sections: experimental and prediction. This approach allows for predictions in the Qorveh region based on data from the experimental area (Bijar and Dehgolan counties), despite the absence of the required data. This method can thus be proposed as a study approach, with related recommendations, for another similar research.
Research Method: This research employed field and library (descriptive-analytical) methods, utilising the Geographic Information System (GIS) for the preparation and interpretation of GIS maps to analyse the settlement habitats of 96 Iron Age sites in eastern Kurdistan (Bijar, Qorveh, Dehgolan). The MaxEnt model was used to predict the distribution of Iron Age sites in eastern Kurdistan.

Data
The present study used a digital elevation model with a spatial resolution of 28 metres. Any change in these data will result in changes in climate, livelihoods, and other factors (Khosrowzadeh & Habibi, 2015: 109). The digital elevation model is used to extract new information such as slope, slope direction, and land curvature. This information is relatively common and significant, and is generally used in predictive models in archaeology. Land curvature data have also been used, which are defined as the rate of slope change (Whitworth, 2011: 469). The prediction model in this paper will be implemented using the principle of maximum entropy (MaxEnt). Such predictive modelling in archaeology requires two types of input data: environmental data (environmental variables that have a direct or indirect effect on the location of historical sites based on archaeological studies) and data related to archaeological sites, also known as presence data. The study area covers the political geography of Bijar, Qorveh, and Dehgolan counties. This study aims to make the most accurate prediction of Iron Age archaeological sites in Qorveh county using presence data (sites) from surrounding areas such as Bijar and Dehgolan counties. Given the similar climate and landscape in the eastern part of Iranian Kurdistan, the prediction of site formation locations in Qorveh County will be presented based on the MaxEnt prediction model.

Discussion
The final result of the prediction model for the eastern part of Kurdistan was based on the frequency ratio (FR) of the land cover and land use variables, which were among the most influential factors in the model. Their impact coefficients were estimated to be 24.3 and 32.6, respectively. Based on the classification of the forecast map, the low-desirability region covers the largest area within the forecast range, comprising 72% of the total. In contrast, better results can be observed due to the reduction in the area of regions in the high-desirability group. These regions, categorised as very high and high-desirability groups, comprise 10.5 percent and 7.5 percent of the total area, respectively. In contrast, it includes the largest number of areas, accounting for 89 percent of the total. These areas comprise 57 and 29 areas, respectively. While the areas with the highest potential are highlighted, they significantly reduce the area available for archaeological investigation.

Conclusion
MaxEnt modelling requires the use of presence data (areas). For this purpose, the prediction model is defined to include two categories of areas. First, the experimental area contains presence data (areas) as well as environmental factors and variables to configure the prediction model. Second: Prediction area; this section and perspective include the city of Qorveh in the eastern part of Kurdistan. The experimental area for this modelling contains 96 presence data points (areas) with an Iron Age chronology. Of these, 25% were used as test data and 75% as training data. Modelling with the MaxEnt method identifies the most influential variables by examining each one. Factors such as vegetation cover, land use, distance from the village, and distance from water sources are among the most influential variables on the model results. In this case, MaxEnt statistical analysis of other variables is also presented. Examination of the altitude variable shows that it has the greatest impact on sites within the altitude range of 1378–1400. The greatest impact of rivers on the sites occurred at a distance of 1000 metres. From 1000 to 3000 metres, the impact was least, but from 3000 to 5000 metres, the influence on site location became significant again. It has been found that at a distance of 2000 metres from villages, the likelihood of site formation is greater than at greater distances. The prediction map is divided into four groups based on the specified threshold value mentioned earlier: very high, high, medium, and low suitability areas. According to this division, the very high suitability area covers 10.5% of the total model area, and 59% of the sites (occurrence data) are located within this area. The high, medium, and low suitability areas include 30%, 6.5%, and 4.5% of the sites within these areas, respectively. Given that the very high and low suitability prediction areas are small but contain the largest percentage of sites, the model can be considered predictive.